🧠 Introduction

Gaming has always fascinated me, not just as a player but as a developer. When I heard about the Amazon Q CLI Challenge, I knew this was my chance to combine innovation, AI, and gaming. This blog shares my journey of building “Emoji Dodge”, an interactive terminal-based survival game, with the help of Amazon Q CLI and PyGame.

🎮 GitHub Repository: github.com/parthibCodes/emojiDodge

🛠️ What is Amazon Q CLI?

Amazon Q CLI is Amazon's generative AI assistant for developers, directly available in your terminal. Think of it like ChatGPT but built right into your command-line interface. You can use it to:

Generate and debug code
Explain libraries and frameworks
Scaffold full projects
Answer any programming questions — all without leaving your terminal

This makes it perfect for rapidly prototyping ideas like games!

🎯 Project Idea: Emoji Dodge

I wanted to build a game that’s:

Visually fun
Easy to play but hard to master
Enhanced with powerups, combos, and emotional feedback

That’s how Emoji Dodge was born. You play as a quirky emoji dodging falling obstacles while collecting powerups and saviors.

🧩 Features of the Game

🧍‍♂️ Play as different emoji avatars like 😎, 🐱, 🦸‍♂️
🧱 Dodge obstacles raining from the top
❤️ Lives system with visual feedback
🧠 Combo bonus system for skilled dodging
🌑 Day/Night mode switching every 30 seconds
🕹️ Slow-motion powerup and fake saviors
💀 Game over screen with score stats and emojis
🔁 Restart with a simple key press
🎡 Spin wheel integration (work-in-progress)

🤖 Using Amazon Q CLI

Here’s how I used Amazon Q CLI in my workflow:

🔍 1. Installing Q CLI and PyGame

Installed Amazon Q CLI by following the guide for Windows (also available for Linux)
Installed PyGame using:
```
  pip install pygame
```

💬 2. Chatting with Amazon Q

I used Amazon Q to:

Get PyGame boilerplate code
Troubleshoot bugs in the main game loop
Get suggestions for improving UX like overlay effects, combo systems, etc.
Understand how to handle frame rates, sprite rendering, and events

💡 Amazon Q CLI’s help was incredibly contextual and efficient. Unlike switching back and forth to a browser, I got answers where I coded — in my terminal.

🎨 Gameplay Demo

You start the game dodging falling blocks using arrow keys. As you progress, saviors appear that can increase lives — but some are fake. The background switches from day to night every 30 seconds, adding visual variety. If you lose all your lives, a game over screen fades in with cool emoji and your final score.

📦 Repo and Code

GitHub: parthibCodes/emojiDodge
Built with: Python + PyGame + Amazon Q CLI
Structure:
```
  main.py
  assets/
  README.md
```

🧪 What I Learned

💡 How powerful generative AI can be when integrated with terminal workflows
🧱 Better code structure using Amazon Q’s suggestions
🎮 Improved my understanding of game loops, state management, and PyGame’s surface system
🧑‍🎨 Gained confidence in combining creativity + code

🔗 Get Involved

You can try out the game by cloning the repo:

clone https://github.com/parthibCodes/emojiDodge
cd emojiDodge
python main.py

Also, join the Amazon Q CLI challenge and build your own game using just prompts and innovation!

📢 Final Step: #AmazonQCLI

This post is part of my entry to the #AmazonQCLI challenge. If you’re a developer looking to explore how AI can level up your productivity, I strongly recommend giving it a shot.

Let’s build the future of development — right from our terminals!

🧵 Connect with Me

🧑‍💻 GitHub: @parthibCodes
💬 Reach out if you want to collaborate on cool tech + AI projects!

🚀 Building “Emoji Dodge” with Amazon Q CLI and PyGame — My Experience in the Amazon Q Challenge